
GCP ARCHITECT / LEAD ENGINEER
CANDIDATE WILL BE DEPLOYED IN A FINANCIAL CAPTIVE ORGANIZATION @ PUNE (KHARADI)
Below are the job Details :-
Experience 10 to 18 years
Mandatory skills –
- data migration,
- data flow
The ideal candidate for this role will have the below experience and qualifications:
- Experience of building a range of Services in a Cloud Service provider (ideally GCP)
- Hands-on design and development of Google Cloud Platform (GCP), across a wide range of GCP services including hands on experience of GCP storage & database technologies.
- Hands-on experience in architecting, designing or implementing solutions on GCP, K8s, and other Google technologies. Security and Compliance, e.g. IAM and cloud compliance/auditing/monitoring tools
- Desired Skills within the GCP stack - Cloud Run, GKE, Serverless, Cloud Functions, Vision API, DLP, Data Flow, Data Fusion
- Prior experience of migrating on-prem applications to cloud environments. Knowledge and hands on experience on Stackdriver, pub-sub, VPC, Subnets, route tables, Load balancers, firewalls both for on premise and the GCP.
- Integrate, configure, deploy and manage centrally provided common cloud services (e.g. IAM, networking, logging, Operating systems, Containers.)
- Manage SDN in GCP Knowledge and experience of DevOps technologies around Continuous Integration & Delivery in GCP using Jenkins.
- Hands on experience of Terraform, Kubernetes, Docker, Stackdriver, Terraform
- Programming experience in one or more of the following languages: Python, Ruby, Java, JavaScript, Go, Groovy, Scala
- Knowledge or experience in DevOps tooling such as Jenkins, Git, Ansible, Splunk, Jira or Confluence, AppD, Docker, Kubernetes
- Act as a consultant and subject matter expert for internal teams to resolve technical deployment obstacles, improve product's vision. Ensure compliance with centrally defined Security
- Financial experience is preferred
- Ability to learn new technologies and rapidly prototype newer concepts
- Top-down thinker, excellent communicator, and great problem solver
Exp:- 10 to 18 years
Location:- Pune
Candidate must have experience in below.
- GCP Data Platform
- Data Processing:- Data Flow, Data Prep, Data Fusion
- Data Storage:- Big Query, Cloud Sql,
- Pub Sub, GCS Bucket

About MNC Pune based IT company
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Required skills and experience: · Solid experience working in Big Data ETL environments with Spark and Java/Scala/Python · Strong experience with AWS cloud technologies (EC2, EMR, S3, Kinesis, etc) · Experience building monitoring/alerting frameworks with tools like Newrelic and escalations with slack/email/dashboard integrations, etc · Executive-level communication, prioritization, and team leadership skills
We are looking out for a technically driven "ML OPS Engineer" for one of our premium client
COMPANY DESCRIPTION:
Key Skills
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
We are looking out for a technically driven "Full-Stack Engineer" for one of our premium client
COMPANY DESCRIPTION:
Qualifications
• Bachelor's degree in computer science or related field; Master's degree is a plus
• 3+ years of relevant work experience
• Meaningful experience with at least two of the following technologies: Python, Scala, Java
• Strong proven experience on distributed processing frameworks (Spark, Hadoop, EMR) and SQL is very
much expected
• Commercial client-facing project experience is helpful, including working in close-knit teams
• Ability to work across structured, semi-structured, and unstructured data, extracting information and
identifying linkages across disparate data sets
• Confirmed ability in clearly communicating complex solutions
• Understandings on Information Security principles to ensure compliant handling and management of
client data
• Experience and interest in Cloud platforms such as: AWS, Azure, Google Platform or Databricks
• Extraordinary attention to detail
● Able contribute to the gathering of functional requirements, developing technical
specifications, and project & test planning
● Demonstrating technical expertise, and solving challenging programming and design
problems
● Roughly 80% hands-on coding
● Generate technical documentation and PowerPoint presentations to communicate
architectural and design options, and educate development teams and business users
● Resolve defects/bugs during QA testing, pre-production, production, and post-release
patches
● Work cross-functionally with various bidgely teams including: product management,
QA/QE, various product lines, and/or business units to drive forward results
Requirements
● BS/MS in computer science or equivalent work experience
● 2-4 years’ experience designing and developing applications in Data Engineering
● Hands-on experience with Big data Eco Systems.
● Hadoop,Hdfs,Map Reduce,YARN,AWS Cloud, EMR, S3, Spark, Cassandra, Kafka,
Zookeeper
● Expertise with any of the following Object-Oriented Languages (OOD): Java/J2EE,Scala,
Python
● Strong leadership experience: Leading meetings, presenting if required
● Excellent communication skills: Demonstrated ability to explain complex technical
issues to both technical and non-technical audiences
● Expertise in the Software design/architecture process
● Expertise with unit testing & Test-Driven Development (TDD)
● Experience on Cloud or AWS is preferable
● Have a good understanding and ability to develop software, prototypes, or proofs of
concepts (POC's) for various Data Engineering requirements.
Responsibilities:
● Designing, building and maintaining efficient, reusable, and reliable architecture and code. ● Participate in the architecture and system design discussions
● Independently perform hands on development/coding and unit testing of the applications
● Collaborate with the development and AI teams and build individual components into complex enterprise web systems
● Work in a team environment with product, frontend design, production operation, QE/QA and cross functional teams to deliver a project throughout the whole software development cycle
● Architect and implement CI/CD strategy for EDP
● Implement high velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred) ● Designing, building and maintaining efficient, reusable, and reliable architecture and code.
● Ensure the best possible performance and quality of high scale web applications and services ● To identify and resolve any performance issues
● Keep up to date with new technology development and implementation
● Participate in code review to make sure standards and best practices are met
● Migrate data from traditional relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift
● Migrate data from AWS Dynamodb to relational database such as PostgreSQL
● Migrate data from APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift
● Work closely with the Data Scientist leads, CTO, Product, Engineering, DevOps and other members of the Ai Science teams
● Collaborate with the product team, share feedback from project implementations and influence the product roadmap.
● Be comfortable in a highly dynamic, agile environment without sacrificing the quality of work products.
Position Requirements:
● Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience
● 5+ years of experience as Data application developer
● AWS Solutions Architect or AWS Developer Certification preferred
● Experience implementing software applications supporting data lakes, data warehouses and data applications on AWS for large enterprises
● Solid Programming experience with Python, Shell scripting and SQL
● Solid experience of AWS services such as CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DataSync, DMS, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
● Solid experience implementing solutions on AWS based data lakes.
● Experience in AWS data lake/data warehouse/business analytics/
● Experience in system analysis, design, development, and implementation of data ingestion pipeline in AWS
● Knowledge of ETL/ELT
● End-to-end data solutions (ingest, storage, integration, processing, access) on AWS ● Experience developing business applications using NoSQL/SQL databases.
● Experience working with Object stores(S3) and JSON is must have
● Should have good experience with AWS Services – Glue, Lambda, Step Functions, SQS, DynamoDB, S3, Redshift, RDS, Cloudwatch and ECS.
● Should have hands-on experience with Python, Django
● Great knowledge of Data Science models
● Plus to have knowledge on Snowflake
Nice to have:
● Solid experience in AWS AI solutions such Recognition, Comperhind and Transcribe
● Python, NodeJS, .NetCore, C#, Reactjs, RestAPI, Microservices, Postman, GraphQL, Mongo, Linux, Javascript, HTML5, CSS, Django
For direct application fill the Form: https://forms.gle/z1Zhz32oHkNmANFV8
The thrill of working at a start-up that is starting to scale massively is something else. Simpl (FinTech startup of the year - 2020) was formed in 2015 by Nitya Sharma, an investment banker from Wall Street and Chaitra Chidanand, a tech executive from the Valley, when they teamed up with a very clear mission - to make money simple so that people can live well and do amazing things. Simpl is the payment platform for the mobile-first world, and we’re backed by some of the best names in fintech globally (folks who have invested in Visa, Square and Transferwise), and
has Joe Saunders, Ex Chairman and CEO of Visa as a board member.
Everyone at Simpl is an internal entrepreneur who is given a lot of bandwidth and resources to create the next breakthrough towards the long term vision of “making money Simpl”. Our first product is a payment platform that lets people buy instantly, anywhere online, and pay later. In
the background, Simpl uses big data for credit underwriting, risk and fraud modelling, all without any paperwork, and enables Banks and Non-Bank Financial Companies to access a whole new consumer market.
In place of traditional forms of identification and authentication, Simpl integrates deeply into merchant apps via SDKs and APIs. This allows for more sophisticated forms of authentication that take full advantage of smartphone data and processing power
Skillset:
Workflow manager/scheduler like Airflow, Luigi, Oozie
Good handle on Python
ETL Experience
Batch processing frameworks like Spark, MR/PIG
File formats: parquet, JSON, XML, thrift, avro, protobuff
Rule engine (drools - business rule management system)
Distributed file systems like HDFS, NFS, AWS, S3 and equivalent
Built/configured dashboards
Nice to have:
Data platform experience for eg: building data lakes, working with near - realtime
applications/frameworks like storm, flink, spark.
AWS
File encoding types: Thrift, Avro, Protobuff, Parquet, JSON, XML
HIVE, HBASE
Must Have Skills:
- Solid Knowledge on DWH, ETL and Big Data Concepts
- Excellent SQL Skills (With knowledge of SQL Analytics Functions)
- Working Experience on any ETL tool i.e. SSIS / Informatica
- Working Experience on any Azure or AWS Big Data Tools.
- Experience on Implementing Data Jobs (Batch / Real time Streaming)
- Excellent written and verbal communication skills in English, Self-motivated with strong sense of ownership and Ready to learn new tools and technologies
Preferred Skills:
- Experience on Py-Spark / Spark SQL
- AWS Data Tools (AWS Glue, AWS Athena)
- Azure Data Tools (Azure Databricks, Azure Data Factory)
Other Skills:
- Knowledge about Azure Blob, Azure File Storage, AWS S3, Elastic Search / Redis Search
- Knowledge on domain/function (across pricing, promotions and assortment).
- Implementation Experience on Schema and Data Validator framework (Python / Java / SQL),
- Knowledge on DQS and MDM.
Key Responsibilities:
- Independently work on ETL / DWH / Big data Projects
- Gather and process raw data at scale.
- Design and develop data applications using selected tools and frameworks as required and requested.
- Read, extract, transform, stage and load data to selected tools and frameworks as required and requested.
- Perform tasks such as writing scripts, web scraping, calling APIs, write SQL queries, etc.
- Work closely with the engineering team to integrate your work into our production systems.
- Process unstructured data into a form suitable for analysis.
- Analyse processed data.
- Support business decisions with ad hoc analysis as needed.
- Monitoring data performance and modifying infrastructure as needed.
Responsibility: Smart Resource, having excellent communication skills
Job Description:
Experience - 2 to 5 Years
- Sound understanding of Google Cloud Platform
- Should have worked on Big Query, Workflow or Composer
- Experience of migrating to GCP and integration projects on large-scale environments
- ETL technical design, development and support
- Good in SQL skills and Unix Scripting
- Programming experience with Python, Java or Spark would be desirable, but not essential
- Good Communication skills .
- Experience of SOA and services-based data solutions, would be advantageous

